For starters, they try to find out the solutions (well, properties and the behaviour of those solutions without actually acquiring the mathematical expression for the solution) of differential equations without actually solving the diff equations. I do not know if you have ever heard of BIFURCATIONS and Bifurcation Theory
I had an intro course on this in my second year at the university.

Any system with feedback will behave chaotically (basically, since positive feedback acts as a sort of memory).

Marlon mentioned a bottom up approach, starting with the equations, but many experimentalists study chaos from the top down, that is, making direct observations of chaos and attempting to quantify their observations and relate those quantities back to system parameters.

Chaos is commonly characterised by defining the dimension of the chaos and the Lyapunov exponent (the rate of divergence of two nearly identical trajectories in the phase space of the system). These two quantities are extremely difficult to calculate and require elaborate computations to do so.

Studying a chaotic system essentially involves the calculation of these two parameters. Chaotic systems usually have several regions of chaos, noticable changes in the behaviour of the system, depending on the amount of positive feedback. By knowing what parameters give what type of chaos, the chaos in a system can be actively controlled.

coo, thx for the replies...is chaotic theory/dynamicalsystems/bifurcation theory(marlon, yeah i know bifurcation, funny how it applies to psych) (ie using the billiard tables system in 3D environment?) used in QM or AP alot or are there very few researchers who use it?

Ah, yes it does turn up in Astrophysics. Here are two examples I have come across.

- Bistability in organic molecular clouds.
- When one includes the gas giants when analysing the motion of the solar system, the small effect of the gas giants can induce a choatic wobble in the earths orbit that may be responsible for long term climate change. I think there was an article in New Scientist on this topic a while ago.

For starters, they try to find out the solutions (well, properties and the behaviour of those solutions without actually acquiring the mathematical expression for the solution) of differential equations without actually solving the diff equations. I had an intro course on this in my second year at the university.

regards
marlon

Well you are talking about Picard's iteration method,and similar things!
But they have limited application,they can't approximate every diff. eqn.

If I remember correctly, the mathematical study of chaos was brought into the forefront of applied maths when it was pointed out that a typical set of diff.eqs. used in meteorology was inherently chaotic.
Meteorology is a field dominated by classical physics modelling (and no discernible improvement would be found if you were to try a QM or relativistic approach).

If I remember correctly, the mathematical study of chaos was brought into the forefront of applied maths when it was pointed out that a typical set of diff.eqs. used in meteorology was inherently chaotic.
Meteorology is a field dominated by classical physics modelling (and no discernible improvement would be found if you were to try a QM or relativistic approach).

Yes, i once studied the application of numerical calculus in meteorology. More specifically the contribution of Lorentz. This was just an example, in my course, of how this stuff can be used in real life. Look at page 9 and chapter 1.4 of this site